Apparatus and methods for screening, diagnosis and monitoring of respiratory disorders

ABSTRACT

A device that may include, or communicate with, sensors such as an electrocardiogram (ECG) sensor, an accelerometer, and/or a photoplethysmograph (PPG) detects sleep-disordered breathing (SDB) events of a patient based on signals from the sensors. The device may have a processor configured to make the detection(s). In an example, the processor may access a memory with processor control instructions. The instructions may be adapted to configure the processor to carry out the detection methodology. The method may include analysing an ECG data of the patient from a signal generated by the ECG sensor, pulse oximetry data of the patient from a signal generated by the PPG, and a three-dimensional (3D) accelerometry data of the patient from a signal generated by the accelerometer to detect the SDB events. The device and methods may be used for screening, diagnosis and monitoring of respiratory disorders.

1 CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation of U.S. application Ser. No.16/340,905, filed Apr. 10, 2019, issued as U.S. Pat. No. 11,350,874,which is a national phase entry under 35 U.S.C. § 371 of InternationalApplication No. PCT/AU2017/051091, filed Oct. 10, 2017, published inEnglish, which claims priority from Australian Application No.2016904105, filed Oct. 11, 2016, all of which are incorporated herein byreference.

2 BACKGROUND OF THE TECHNOLOGY 2.1 Field of the Technology

The present technology relates to one or more of the screening,diagnosis, monitoring, treatment, prevention and amelioration ofrespiratory-related disorders. The present technology also relates tomedical devices or apparatus, and their use.

2.2 Description of the Related Art 2.2.1 Human Respiratory System andits Disorders

The respiratory system of the body facilitates gas exchange.

The nose and mouth form the entrance to the airways of a patient. Theairways include a series of branching tubes, which become narrower,shorter and more numerous as they penetrate deeper into the lung. Theprime function of the lung is gas exchange, allowing oxygen to move fromthe air into the venous blood and carbon dioxide to move out. Thetrachea divides into right and left main bronchi, which further divideeventually into terminal bronchioles. The bronchi make up the conductingairways, and do not take part in gas exchange. Further divisions of theairways lead to the respiratory bronchioles, and eventually to thealveoli. The alveolated region of the lung is where the gas exchangetakes place, and is referred to as the respiratory zone. See“Respiratory Physiology”, by John B. West, Lippincott Williams &Wilkins, 9th edition published 2012.

A range of respiratory disorders exist. Certain disorders may becharacterised by particular events, e.g. apneas, hypopneas, andhyperpneas.

Obstructive Sleep Apnea (OSA), a form of Sleep Disordered Breathing(SDB), is characterized by events including occlusion or obstruction ofthe upper air passage during sleep. It results from a combination of anabnormally small upper airway and the normal loss of muscle tone in theregion of the tongue, soft palate and posterior oropharyngeal wallduring sleep. The condition causes the affected patient to stopbreathing for periods typically of 30 to 120 seconds in duration,sometimes 200 to 300 times per night. It often causes excessive daytimesomnolence, and it may cause cardiovascular disease and brain damage.The syndrome is a common disorder, particularly in middle agedoverweight males, although a person affected may have no awareness ofthe problem. See U.S. Pat. No. 4,944,310 (Sullivan).

Cheyne-Stokes Respiration (CSR) is another form of sleep disorderedbreathing. CSR is a disorder of a patient's respiratory controller inwhich there are rhythmic alternating periods of waxing and waningventilation known as CSR cycles. CSR is characterised by repetitivede-oxygenation and re-oxygenation of the arterial blood. It is possiblethat CSR is harmful because of the repetitive hypoxia. In some patientsCSR is associated with repetitive arousal from sleep, which causessevere sleep disruption, increased sympathetic activity, and increasedafterload. See U.S. Pat. No. 6,532,959 (Berthon-Jones).

2.2.2 Therapy

Various therapies, such as Continuous Positive Airway Pressure (CPAP)therapy, non-invasive ventilation (NIV) and invasive ventilation (IV)have been used to treat one or more of the above respiratory disorders.

Continuous Positive Airway Pressure (CPAP) therapy has been used totreat Obstructive Sleep Apnea (OSA). The mechanism of action is thatcontinuous positive airway pressure acts as a pneumatic splint and mayprevent upper airway occlusion, such as by pushing the soft palate andtongue forward and away from the posterior oropharyngeal wall. Treatmentof OSA by CPAP therapy may be voluntary, and hence patients may electnot to comply with therapy if they find devices used to provide suchtherapy one or more of: uncomfortable, difficult to use, expensive andaesthetically unappealing.

Non-invasive ventilation (NIV) provides ventilatory support to a patientthrough the upper airways to assist the patient breathing and/ormaintain adequate oxygen levels in the body by doing some or all of thework of breathing. The ventilatory support is provided via anon-invasive patient interface. NIV has been used to treat CSR andrespiratory failure, in forms such as OHS, COPD, NMD and Chest Walldisorders. In some forms, the comfort and effectiveness of thesetherapies may be improved.

Invasive ventilation (IV) provides ventilatory support to patients thatare no longer able to effectively breathe themselves and may be providedusing a tracheostomy tube. In some forms, the comfort and effectivenessof these therapies may be improved.

2.2.3 Treatment Systems

The above-mentioned therapies may be provided by a treatment system ordevice. Such systems and devices may also be used to screen, diagnose,or monitor a condition without treating it.

A treatment system may comprise a Respiratory Pressure Therapy Device(RPT device), an air circuit, a humidifier, and a patient interface.

2.2.3.1 Patient Interface

A patient interface may be used to interface respiratory equipment toits wearer, for example by providing a flow of air to an entrance to theairways. The flow of air may be provided via a mask to the nose and/ormouth, a tube to the mouth or a tracheostomy tube to the trachea of apatient. Depending upon the therapy to be applied, the patient interfacemay form a seal, e.g., with a region of the patient's face, tofacilitate the delivery of gas at a pressure at sufficient variance withambient pressure to effect therapy, e.g., at a positive pressure ofabout 10 cmH₂O relative to ambient pressure. For other forms of therapy,such as the delivery of oxygen, the patient interface may not include aseal sufficient to facilitate delivery to the airways of a supply of gasat a positive pressure of about 10 cmH₂O.

2.2.3.2 Respiratory Pressure Therapy (RPT) Device

A respiratory pressure therapy (RPT) device may be used to deliver oneor more of a number of therapies described above, such as by generatinga flow of air for delivery to an entrance to the airways. The flow ofair may be pressurised. Examples of RPT devices include a CPAP deviceand a ventilator.

2.2.3.3 Humidifier

Delivery of a flow of air without humidification may cause drying ofairways. The use of a humidifier with an RPT device and the patientinterface produces humidified gas that minimizes drying of the nasalmucosa and increases patient airway comfort. In addition in coolerclimates, warm air applied generally to the face area in and about thepatient interface is more comfortable than cold air.

2.2.4 Screening/Diagnosis/Monitoring Systems

Screening and diagnosis generally describe the identification of adisorder from its signs and symptoms. Screening typically gives atrue/false result indicating whether or not a patient's disorder issevere enough to warrant further investigation, while diagnosis mayresult in clinically actionable information. Screening and diagnosistend to be one-off processes, whereas monitoring the progress of adisorder can continue indefinitely. Some screening/diagnosis systems aresuitable only for screening/diagnosis, whereas some may also be used formonitoring.

Polysomnography (PSG) is a conventional system for diagnosis/monitoringof cardio-pulmonary disorders, and typically involves expert clinicalstaff to apply the system. PSG typically involves the placement of 15 to20 contact sensors on a person in order to record various biosignalssuch as electroencephalography (EEG), electrocardiography (ECG),electrooculograpy (EOG), electromyography (EMG), etc. PSG for sleepdisordered breathing has involved two nights of observation of a patientin a clinic, one night of pure diagnosis and a second night of titrationof treatment parameters by a clinician. Clinical experts may be able todiagnose or monitor patients adequately based on visual observation ofPSG signals. However, there are circumstances where a clinical expertmay not be available, or a clinical expert may not be affordable. PSG istherefore expensive and inconvenient. In particular it is unsuitable forin-home diagnosis/monitoring.

A more convenient screening/diagnosis/monitoring system for home usecomprises a nasal cannula, a pressure sensor, a processing device, andrecording means. A nasal cannula is a device comprising two hollowopen-ended projections that are configured to be inserted non-invasivelya little way into a patient's nares so as to interfere as little aspossible with the patient's respiration. The hollow projections are influid communication with a pressure transducer via a Y-shaped tube. Thepressure transducer provides a data signal representative of thepressure at the entrance to the patient's nares (the nasal pressure). Ithas been shown that a nasal pressure signal is a satisfactory proxy forthe nasal flow rate signal generated by a flow rate transducer in-linewith a sealed nasal mask, in that the nasal pressure signal iscomparable in shape to the nasal flow rate signal. The processing devicemay be configured to analyse the nasal pressure signal from the pressuretransducer in real time or near real time to detect and classify SDBevents in order to monitor the patient's condition. Screening ordiagnosis may require similar analysis but not necessarily in real timeor near real time. The recording means is therefore configured to recordthe nasal pressure signal from the pressure transducer for lateroff-line or “batch” analysis by the processing device forscreening/diagnosis purposes.

However, such pressure-based systems are not always able to reliablydistinguish CSR from the repeated occurrences of obstructive apneascharacteristic of OSA. Other sensor modalities have therefore beenemployed to supplement or replace the nasal pressure signal in moresophisticated screening/diagnosis/monitoring systems. However, suchsystems start to resemble full PSG as more sensors are added, with allthe above-mentioned disadvantages. It is desirable to utilise acombination of sensors that are as unobtrusive as possible whilemaintaining accuracy of SDB screening/diagnosis/monitoring.

3 BRIEF SUMMARY OF THE TECHNOLOGY

The present technology is directed towards providing medical devicesused in the screening, diagnosis, or monitoring of respiratory disordershaving one or more of improved comfort, cost, efficacy, ease of use andmanufacturability.

Some versions of the present technology may include a device having anelectrocardiogram (ECG) sensor; an accelerometer; and aphotoplethysmograph (PPG). The device may also include a processor. Thedevice may also include a memory. The memory may include processorcontrol instructions adapted to configure the processor to detectsleep-disordered breathing (SDB) events of a patient. The processor,such as with the instructions, may be configured to control an analysisof ECG data of the patient from a signal generated by the ECG sensor,pulse oximetry data of the patient from a signal generated by the PPG,and three-dimensional (3D) accelerometry data of the patient from asignal generated by the accelerometer. The processor, such as with theinstructions, may also be configured to detect the SDB events based onthe analysis.

In some cases, the analysis may estimate a sleep stage of the patientfrom the ECG data. The device may also include a temperature sensor. Theanalysis that estimates the sleep stage may evaluate temperature datafrom a signal generated by the temperature sensor. The temperature datamay represent temperature of skin of the patient. In some cases, thedevice may include a galvanic skin response (GSR) sensor. The analysisto estimate the sleep stage may evaluate sympathetic activity data ofthe patient from a signal generated by the GSR sensor. In some cases,with the instructions, the processor may be further configured toclassify the detected SDB events into apneas and hypopneas, and/or intoopen and closed airway events.

In some cases, the device may include a galvanic skin response (GSR)sensor. With the instructions, the processor may be configured toclassify the detected SDB events by evaluation of sympathetic activitydata of the patient from a signal generated by the GSR sensor. Thedevice may also include an acoustic sensor. With the instructions, theprocessor may be configured to classify the detected SDB events byevaluation of acoustic data representing heart sound of the patient froma signal generated by the acoustic sensor. In some versions, the devicemay be configured as a patch adapted to be worn on skin of a chest ofthe patient.

Some versions of the present technology may include a method ofdetecting sleep-disordered breathing (SDB) events of a patient. Themethod may include controlling, in one or more processors, an analysisof electrocardiogram (ECG) data of the patient from a signal generatedby an ECG sensor, pulse oximetry data of the patient from a signalgenerated by a photoplethysmograph (PPG), and three-dimensional (3D)accelerometry data of the patient from a signal generated by anaccelerometer. The method may include detecting, in the one or moreprocessors, SDB events based on the analysis, to generate an outputindication of SDB events.

In some cases, the analysis of the ECG data may include removingartefacts from the ECG data to produce artefact-removed ECG data.Removing artefacts from the ECG data may include identifying portions ofthe ECG data that differ from a typical portion. Analysing the ECG datamay include estimating a sleep stage of the patient based on theartefact-removed ECG data. Estimating a sleep stage may includeevaluating patient skin temperature data from a temperature signalgenerated by a temperature sensor. Estimating a sleep stage may includeevaluating sympathetic activity data of the patient from a signalgenerated by a galvanic skin response (GSR) sensor. The analysis of theECG data may include estimating a respiratory rate from theartefact-removed ECG data. The analysis of the ECG data may includeextracting a respiratory-related component from the artefact-removed ECGdata. The analysis of the 3D accelerometry data may include estimating aposture of the patient from the 3D accelerometry data. The analysis ofthe 3D accelerometry data may include estimating a respiratory effort ofthe patient from the 3D accelerometry data. The analysis of the 3Daccelerometry data may include computing an activity index of thepatient from the 3D accelerometry data. The activity index may representgross bodily motion of the patient.

In some cases, the detecting of the SDB events may include: extractingfeatures, and discriminating between normal breathing and SDB events byapplying a classifier to the features. The method may include, in theone or more processors, classifying the detected SDB events into apneasand hypopneas, and into open and closed airway events. In some cases,the classifying the detected SDB events may evaluate the pulse oximetrydata from the PPG. The classifying the detected SDB events may evaluatesympathetic activity data of the patient from a signal generated by agalvanic skin response (GSR) sensor. The classifying the detected SDBevents may evaluate acoustic data representing heart sound of thepatient from a signal generated by an acoustic sensor. The classifyingthe detected SDB events may include segmenting the acoustic data intophases of each heart cycle, and extracting heart sound features from thesegmented acoustic data. The classifying the detected SDB events may usethe heart sound features.

In some cases, the method may include detecting, in the one or moreprocessors, Cheyne-Stokes respiration (CSR) from classified SDB eventsfrom the classifying. The detecting CSR may include template matching ofa respiratory-related component extracted from the ECG data. The methodmay include controlling, with the one or more processors, (a) generatingthe signal by the ECG sensor, (b) generating the signal by thephotoplethysmograph (PPG), and (c) generating the signal by theaccelerometer. The method may include determining or controlling, withthe one or more processors, a change to a therapy provided by a therapydevice based on the output indication of SDB events.

In some cases, a processor-readable medium may have stored thereonprocessor-executable instructions which, when executed by a processor,cause the processor to detect detecting sleep-disordered breathing (SDB)events according to any of the methodologies described herein.

Some versions of the present technology may include a system. The systemmay include an electrocardiogram (ECG) sensor; an accelerometer; and aphotoplethysmograph (PPG). The system may include one or moreprocessors. The system may include a memory having processor controlinstructions adapted to configure the one or more processors to detectsleep-disordered breathing (SDB) events of a patient. The one or moreprocessors, such as with the instructions, may be configured to controlan analysis of ECG data of the patient from a signal generated by theECG sensor, pulse oximetry data of the patient from a signal generatedby the PPG, and three-dimensional (3D) accelerometry data of the patientfrom a signal generated by the accelerometer. The one or moreprocessors, such as with the instructions, may be configured to detectthe SDB events based on the analysis.

In some cases, the ECG sensor, the accelerometer, the PPG, the memory,and the one or more processors are co-located in one device. In somecases, the ECG sensor, the accelerometer, and the PPG are co-located inone device, and the one or more processors and the memory are locatedremotely from the device. In some cases, the device of the system mayinclude a communication interface through which the device may beconfigured to communicate with the one or more processors. The devicemay be configured as a patch adapted to be worn on skin of a chest ofthe patient.

Some versions of the present technology may include an apparatus. Theapparatus may include means for generating electrocardiogram (ECG) dataof a patient. The apparatus may include means for generatingthree-dimensional (3D) accelerometry data of the patient. The apparatusmay include means for generating pulse oximetry data of the patient. Theapparatus may include means for analysing the ECG data of the patient,the pulse oximetry data of the patient, and the 3D accelerometry data ofthe patient to detect sleep-disordered breathing (SDB) events of thepatient.

In some cases, the apparatus may include means for estimating sleepstage from the ECG data. The apparatus may include means for generatingtemperature data, wherein the means for estimating sleep stage estimatessleep stage based on the temperature data. The apparatus may includemeans for generating sympathetic activity data, wherein the means forestimating sleep stage estimates sleep stage based on the sympatheticactivity data. The apparatus may include means for classifying detectedSDB events. The apparatus may include means for generating heart sounddata, wherein the means for classifying classifies the SDB events basedon the heart sound data. The apparatus may include means for removingartefact from the ECG data. The apparatus may include means for mountingthe apparatus to skin of a chest of the patient.

Another aspect of the present technology relates to apparatus andmethods to analyse data from a patch device including ECG contacts, athree-axis accelerometer, an acoustic sensor, and a pulse oximeter, todetect and classify apneas and hypopneas and hence screen, diagnoseand/or monitor SDB. As part of the analysis, the signal processing mayestimate sleep/wake state. The patch sensor may also include atemperature sensor and a galvanic skin response (GSR) sensor whosesignals are incorporated into the analysis to improve the accuracy.

In accordance with another aspect of the present technology, there isprovided a device comprising: an electrocardiogram (ECG) sensor; anaccelerometer; a photoplethysmograph (PPG); a processor; and a memorycomprising instructions adapted to configure the processor to carry outa method of detecting sleep-disordered breathing (SDB) events of apatient. The method comprises analysing an ECG signal of the patientfrom the ECG sensor, pulse oximetry data of the patient from the PPG,and a three-dimensional (3D) accelerometry signal of the patient fromthe accelerometer to detect the SDB events.

In accordance with another aspect of the present technology, there isprovided a method of detecting sleep-disordered breathing (SDB) eventsof a patient. The method comprises analysing an electrocardiogram (ECG)signal of the patient from an ECG sensor, pulse oximetry data of thepatient from a photoplethysmograph (PPG), and a three-dimensional (3D)accelerometry signal of the patient from an accelerometer to detect theSDB events.

The methods, systems, devices and apparatus described herein can provideimproved functioning in a processor, such as of a processor of aspecific purpose computer, respiratory monitor and/or a respiratorytherapy apparatus. Moreover, the described methods, systems, devices andapparatus can provide improvements in the technological field ofautomated management, monitoring and/or treatment of respiratoryconditions, including, for example, sleep disordered breathing.

Of course, portions of the aspects may form sub-aspects of the presenttechnology. Also, various ones of the sub-aspects and/or aspects may becombined in various manners and also constitute additional aspects orsub-aspects of the present technology.

Other features of the technology will be apparent from consideration ofthe information contained in the following detailed description,abstract, drawings and claims.

4 BRIEF DESCRIPTION OF THE DRAWINGS

The present technology is illustrated by way of example, and not by wayof limitation, in the figures of the accompanying drawings, in whichlike reference numerals refer to similar elements including:

4.1 Treatment Systems

FIG. 1 shows a system including a patient 1000 wearing a patientinterface 3000, in the form of nasal pillows, receiving a supply of airat positive pressure from an RPT device 4000. Air from the RPT device4000 is humidified in a humidifier 5000, and passes along an air circuit4170 to the patient 1000. A bed partner 1100 is also shown. The patientis sleeping in a supine sleeping position.

4.2 Respiratory System and Facial Anatomy

FIG. 2 shows an overview of a human respiratory system including thenasal and oral cavities, the larynx, vocal folds, oesophagus, trachea,bronchus, lung, alveolar sacs, heart and diaphragm.

4.3 Patient Interface

FIG. 3 shows a patient interface in the form of a nasal mask inaccordance with one form of the present technology.

4.4 RPT Device

FIG. 4 shows an RPT device in accordance with one form of the presenttechnology.

4.5 Humidifier

FIG. 5A shows an isometric view of a humidifier in accordance with oneform of the present technology.

FIG. 5B shows an isometric view of a humidifier in accordance with oneform of the present technology, showing a humidifier reservoir 5110removed from the humidifier reservoir dock 5130.

4.6 Breathing Waveforms

FIG. 6A shows a model typical breath waveform of a person whilesleeping.

FIG. 6B shows a patient during Non-REM sleep breathing normally over aperiod of about ninety seconds.

FIG. 6C shows polysomnography of a patient before treatment.

FIG. 6D shows patient flow data where the patient is experiencing aseries of total obstructive apneas.

FIG. 6E shows patient data from a patient with Cheyne-Stokesrespiration.

FIG. 6F shows patient data from a patient with another example ofCheyne-Stokes respiration, using the same three channels as in FIG. 6E.

4.7 Screening/Diagnosis/Monitoring Systems

FIG. 7A shows a patient undergoing polysomnography (PSG).

FIG. 7B is a block diagram illustrating a screening/diagnosis/monitoringdevice according to one form of the present technology.

FIG. 8A is a flow chart illustrating a method ofscreening/diagnosing/monitoring SDB making use of the device of FIG. 7Bin one form of the present technology.

FIG. 8B is a flow chart illustrating a method that may be used toimplement the artefact removal step of the method of FIG. 8 in one formof the present technology.

FIG. 9 is a graph illustrating the operation of the artefact removalmethod of FIG. 8B on an example ECG signal.

5 DETAILED DESCRIPTION OF EXAMPLES OF THE TECHNOLOGY

Before the present technology is described in further detail, it is tobe understood that the technology is not limited to the particularexamples described herein, which may vary. It is also to be understoodthat the terminology used in this disclosure is for the purpose ofdescribing only the particular examples discussed herein, and is notintended to be limiting.

The following description is provided in relation to various exampleswhich may share one or more common characteristics and/or features. Itis to be understood that one or more features of any one example may becombinable with one or more features of another example or otherexamples. In addition, any single feature or combination of features inany of the examples may constitute a further example.

5.1 Therapy

In one form, the present technology comprises a method for treating arespiratory disorder comprising the step of applying positive pressureto the entrance of the airways of a patient 1000.

In certain examples of the present technology, a supply of air atpositive pressure is provided to the nasal passages of the patient viaone or both nares.

5.2 Treatment Systems

In one form, the present technology comprises an apparatus or device fortreating a respiratory disorder. The apparatus or device may comprise anRPT device 4000 for supplying pressurised air to the patient 1000 via anair circuit 4170 to a patient interface 3000.

5.3 Patient Interface

A non-invasive patient interface 3000 in accordance with one aspect ofthe present technology comprises the following functional aspects: aseal-forming structure 3100, a plenum chamber 3200, a positioning andstabilising structure 3300, a vent 3400, one form of connection port3600 for connection to air circuit 4170, and a forehead support 3700. Insome forms a functional aspect may be provided by one or more physicalcomponents. In some forms, one physical component may provide one ormore functional aspects. In use the seal-forming structure 3100 isarranged to surround an entrance to the airways of the patient so as tofacilitate the supply of air at positive pressure to the airways.

5.4 RPT Device

An RPT device 4000 in accordance with one aspect of the presenttechnology comprises mechanical, pneumatic, and/or electrical componentsand is configured to execute one or more algorithms. The RPT device 4000may be configured to generate a flow of air for delivery to a patient'sairways, such as to treat one or more of the respiratory conditionsdescribed elsewhere in the present document.

The RPT device may have an external housing 4010, formed in two parts,an upper portion 4012 and a lower portion 4014. Furthermore, theexternal housing 4010 may include one or more panels 4015. The RPTdevice 4000 comprises a chassis 4016 that supports one or more internalcomponents of the RPT device 4000. The RPT device 4000 may include ahandle 4018.

The pneumatic path of the RPT device 4000 may comprise one or more airpath items, e.g., an inlet air filter 4112 and a pressure generatorcapable of supplying air at positive pressure (e.g., a blower 4142).

One or more of the air path items may be located within a removableunitary structure which will be referred to as a pneumatic block 4020.The pneumatic block 4020 may be located within the external housing4010. In one form a pneumatic block 4020 is supported by, or formed aspart of the chassis 4016.

The RPT device 4000 may have an electrical power supply 4210 and one ormore input devices 4220. Electrical components 4200 may be mounted on asingle Printed Circuit Board Assembly (PCBA) 4202.

5.5 Air Circuit

An air circuit 4170 in accordance with an aspect of the presenttechnology is a conduit or a tube constructed and arranged to allow, inuse, a flow of air to travel between two components such as RPT device4000 and the patient interface 3000.

In particular, the air circuit 4170 may be in fluid connection with theoutlet of the pneumatic block 4020 and the patient interface. The aircircuit may be referred to as an air delivery tube. In some cases theremay be separate limbs of the circuit for inhalation and exhalation. Inother cases a single limb is used.

5.6 Humidifier

In one form of the present technology there is provided a humidifier5000 (e.g. as shown in FIG. 5A) to change the absolute humidity of airor gas for delivery to a patient relative to ambient air. Typically, thehumidifier 5000 is used to increase the absolute humidity and increasethe temperature of the flow of air (relative to ambient air) beforedelivery to the patient's airways.

The humidifier 5000 may comprise a humidifier reservoir 5110, ahumidifier inlet 5002 to receive a flow of air, and a humidifier outlet5004 to deliver a humidified flow of air. In some forms, as shown inFIG. 5A and FIG. 5B, an inlet and an outlet of the humidifier reservoir5110 may be the humidifier inlet 5002 and the humidifier outlet 5004respectively. The humidifier 5000 may further comprise a humidifier base5006, which may be adapted to receive the humidifier reservoir 5110 andcomprise a heating element 5240.

5.7 Screening/Diagnosis/Monitoring Systems

5.7.1 Breathing waveforms

FIG. 6A shows a model typical breath waveform of a person whilesleeping. The horizontal axis is time, and the vertical axis isrespiratory flow rate. While the parameter values may vary, a typicalbreath may have the following approximate values: tidal volume, Vt, 0.5litres, inhalation time, Ti, 1.6s, peak inspiratory flow rate, Qpeak,0.4 L/s, exhalation time, Te, 2.4s, peak expiratory flow rate, Qpeak,−0.5 L/s. The total duration of the breath, Ttot, is about 4s. Theperson typically breathes at a rate of about 15 breaths per minute(BPM), with Ventilation, Vent, about 7.5 L/minute. A typical duty cycle,the ratio of Ti to Ttot, is about 40%.

FIG. 6B shows patient data from a patient during non-REM sleep breathingnormally over a period of about ninety seconds comprising about 34breaths, being treated with Automatic PAP, and the mask pressure beingabout 11 cmH₂O. The top channel shows oximetry (oxygen saturation orSpO₂), the scale having a range of saturation from 90 to 99% in thevertical direction. The patient maintained a saturation of about 95%throughout the period shown. The second channel shows quantitativerespiratory airflow, and the scale ranges from −1 to +1 litres persecond in a vertical direction, and with inspiration positive. Thoracicand abdominal movement are shown in the third and fourth channels.

FIG. 6C shows polysomnography of a patient before treatment. There areeleven signal channels from top to bottom with a 6 minute horizontalspan. The top two channels are both EEG (electoencephalogram) fromdifferent scalp locations. Periodic spikes in the second EEG representcortical arousal and related activity. The third channel down issubmental EMG (electromyogram). Increasing activity around the time ofarousals represents genioglossus recruitment. The fourth & fifthchannels are EOG (electro-oculogram). The sixth channel is anelectocardiogram. The seventh channel shows oxygen saturation withrepetitive desaturations to below 70% from about 90%. The eighth channelis respiratory flow rate from a nasal cannula connected to adifferential pressure transducer. Repetitive apneas of 25 to 35 secondsalternate with 10 to 15 second bursts of recovery breathing coincidingwith EEG arousal and increased EMG activity. The ninth channel showsthoracic movement and the tenth shows abdominal movement. The abdomenshows a crescendo of movement over the length of the apnea leading tothe arousal. Both become untidy during the arousal due to gross bodilymovement during recovery hyperpnea. The apneas are thereforeobstructive, and the condition is severe. The lowest channel is posture,and in this example it does not show change.

FIG. 6D shows patient flow rate data where the patient is experiencing aseries of total obstructive apneas. The duration of the recording isapproximately 160 seconds. Flow rates range from about +1 L/s to about−1.5 L/s. Each apnea lasts approximately 10 to 15 seconds.

FIG. 6E shows patient data from a patient with Cheyne-Stokesrespiration. There are three channels: pulse oximetry (SpO₂); a signalindicative of flow rate; and thoracic movement. The data span sixminutes. The signal representative of flow rate was measured using apressure sensor connected to a nasal cannula. The patient exhibitsapneas of about 22 seconds and hyperpneas of about 38 seconds. Thehigher frequency low amplitude oscillation in the flow rate signalduring apnea is cardiogenic.

FIG. 6F shows patient data from a patient with another example ofCheyne-Stokes respiration, using the same three channels as in FIG. 6E.The data span ten minutes. The patient exhibits hyperpneas of about 30seconds and hypopneas of about 30 seconds.

5.7.2 Polysomnography

FIG. 7A shows a patient 1000 undergoing polysomnography (PSG). The PSGsystem illustrated in FIG. 7A comprises a headbox 2000 which receivesand records signals from the following sensors: an EOG electrode 2015;an EEG electrode 2020; an ECG electrode 2025; a submental EMG electrode2030; a snore sensor 2035; a respiratory inductance plethysmogram(thoracic movement sensor) 2040 on a chest band; a respiratoryinductance plethysmogram (abdominal movement sensor) 2045 on anabdominal band; an oro-nasal cannula 2050 with oral thermistor; aphotoplethysmograph (pulse oximeter) 2055; and a body position sensor2060. The electrical signals from the electrodes (2015, 2020, 2025,2030) are referenced to a ground electrode (ISOG) 2010 on the patientsuch as one positioned in the centre of the forehead.

5.7.3 Screening/Diagnosis/Monitoring Patch Device

FIG. 7B is a block diagram illustrating a screening/diagnosis/monitoringdevice 7100 according to one form of the present technology. The device7100 may be configured as a patch, adapted to be worn on the skin of thechest of the patient 1000, preferably on the upper left chest.

The device 7100 comprises multiple biometric sensors 7170 to 7180, eachconfigured to generate a signal representing one or more physiologicalparameters of a patient 1000. The ECG sensor 7170 comprises one or moreelectrical contacts which, when in contact with the skin, generate asignal known as the electrocardiogram (ECG or EKG) representative of theelectrical activity of the heart. The three-axis accelerometer 7172generates a three-component signal (referred to as the 3D accelerometrysignal), each component of which represents the acceleration of thedevice 7100 along a corresponding orthogonal axis. In a typicalorientation, the z-axis is perpendicular to the skin. The x- and y-axesmay be aligned in any direction in the plane of the skin. However, theorientation of the x- and y-axes in relation to the main axes of thebody (superior-inferior and medial-lateral) may be taken into account bythe accelerometry signal analysis (described below). When theaccelerometer 7172 is at rest, it can detect the influence of gravityand hence provide an absolute vertical direction. Thephotoplethysmograph (PPG or pulse oximeter) 7174 uses light to estimatethe blood oxygen saturation (SpO₂, or oximetry) of the patient, usuallyrepresented as a percentage (%). The temperature sensor 7176 generates asignal representing the temperature of the patient's skin. The acousticsensor 7178 (e.g. a microphone) generates a signal representing theheart sounds of the patient 1000. The galvanic skin response (GSR)sensor 7180 generates a signal representative of the conductivity of theskin in the region of the device 7100, which in turn is indicative ofsympathetic nervous system activity (which among other physiologicaleffects activates the sweat glands).

The device 7100 also comprises an input/output (I/O) interface such as asensor interface 7160 (e.g., with multiple ports) that may receive thesignals from the sensors 7170 to 7180 during ascreening/diagnosis/monitoring session. The signals from the sensors maybe generated by the sensors in analog or digital form. Thus, theinterface may have analog and/or digital ports. For example, one or moreof the sensor signals may arrive at the sensor interface 7160 assequences of discrete samples (“sensor data”) at respective samplingrates. The sensor interface 7160 may discretise those of the sensorsignals not arriving in this form into respective sequences of discretesamples at respective sampling rates, so that all signals provided bythe sensor interface 7160 are in discrete form.

In some cases, the device may be formed with or include a controller,such as a microcontroller with a processor or CPU. In some cases, thecontroller may be formed with a microprocessor. Thus, the device 7100typically contains a processor 7110 configured to carry out the methodsdescribed herein such as with encoded instructions. The device 7100 mayalso contain a non-transient computer readable memory/storage medium7130. The memory 7130 may be the internal memory of the device 7100,such as RAM, flash memory or ROM. In some implementations, memory 7130may also be a removable or external memory linked to the device 7100,such as an SD card, server, USB flash drive or optical disc, forexample. In other implementations, memory 7130 can be a combination ofexternal and internal memory. The contents of the memory 7130 includestored data 7140 and processor control instructions (code) 7150 adaptedto configure the processor 7110 to perform certain tasks. Stored data7140 can include sensor data from sensor interface 7160 during asession, and other data that is provided as a component part of anapplication. Processor control instructions 7150 can also be provided asa component part of an application. The processor 7110 is adapted toread the code 7150 from the memory 7130 and execute the encodedinstructions. In particular, the code 7150 may contain instructions thatconfigure the processor 7110 to carry out methods of processing thesensor data signals from the sensor interface 7160. One such method maybe to record the sensor data for the session in the memory 7130 as data7140. Another such method may be to analyse the session recording toextract SDB features. One such analysis method is described in detailbelow. The processor 7110 may store the results of such analysis (theSDB features) as data 7140 in the memory 7130.

The device 7100 may also contain a communication interface 7120. Thecode 7150 may contain instructions adapted to configure the processor7110 to communicate with a remote external computing device (not shown)such as an RPT device 4000 via the communication interface 7120. Themode of communication may be wired or wireless. In one suchimplementation, the processor 7110 may transmit the real time orsession-by-session recording information from the data 7140 to theremote computing device via the communication interface 7120. In such animplementation, a processor of the remote computing device may beconfigured to analyse the received session recording to extract SDBfeatures. In another such implementation, the processor 7110 maytransmit the analysis results (e.g., indications of the SDB features orother detected or estimated patient related information) from the data7140 to the remote computing device via the communication interface7120. In yet another such implementation, the processor 7110 maypartially analyse the session data, store and transmit the results ofthe partial analysis to the remote computing device via thecommunication interface 7120, and the processor of the remote computingdevice may complete the analysis to obtain the SDB features.

Alternatively, if the memory 7130 is removable from the device 7100, theremote computing device may be configured to be connected to theremovable memory 7130. In such an implementation, the remote computingdevice may be configured to retrieve the session data from the removablememory 7130 and analyse the session data to extract SDB features.

In the case of transmission of data via the communication interface toan RPT device 4000, the data may serve as a basis for making controlchanges in an automated therapy adjustment process of the RPT device4000 based on the data. For example, based on the extracted SDB featuresand/or sleep state, a therapy change, such as a change to pressure orflow (e.g., an increase or decrease) may be controlled by the RPT device4000.

5.7.4 Signal Analysis

FIG. 8A is a flow chart illustrating example processes that may beimplemented in a method 8000 of screening/diagnosing/monitoring SDBmaking use of the device 7100 in one form of the present technology. Themethod 8000 may be implemented by the processor 7110 of the device 7100,a processor of a remote external computing device in communication withthe device 7100, or a combination of both as described above. The method8000 may be carried out in real time during a session, in which case itis more appropriately described as a monitoring method, or in “batch”mode on recorded data after the session, in which case it is moreappropriately described as a screening or diagnosis method.

Process 8005 removes movement and other artefacts from the ECG signalgenerated by the ECG sensor 7170. Process 8005 may optionally evaluatethe 3D accelerometry signal from the accelerometer 7172 to detect timingof such artefacts for removal of corresponding portions of the ECGsignal based on timing of such detection of artefacts. Such removal mayinclude adjusting the ECG, such as by interpolation, smoothing or othertechnique, to produce an ECG signal that reduces or eliminates theeffect of the artefact.

FIG. 8B is a flow chart illustrating an example method 8100 that may beimplemented to perform the artefact removal process 8005 of the method8000 in one form of the present technology. In this example, the method8100 does not use the 3D accelerometry signal from the accelerometer7172, but is based on the assumption that most portions of the ECGsignal resemble the other portions, and identifies those portions thatdiffer substantially from the typical. The method 8100 starts at process8110, which band-pass filters the ECG signal such as within thefrequency range of about 5 to 40 Hz. Process 8120 then differentiates(e.g., by derivative function) and squares the band-pass filtered ECGsignal (e.g., by squaring function). The next process 8130 finds theupper envelope of the squared derivative of the band-pass filtered ECGsignal.

Process 8140 then works sequentially through a sequence ofnon-overlapping windows of fixed duration into which the envelope ispartitioned. In one implementation, the windows are of duration on theorder of a predetermined number of seconds, (e.g., 30 seconds, 25seconds, 35 seconds, etc.). For each window, process 8140 computes theautocorrelation function of the envelope, up to a lag of a predeterminednumber of samples (e.g., 45 samples). The next process 8150 computes athreshold by averaging the peak values of the autocorrelation functionsover all windows, and dividing by a predetermined number (e.g., 10).Process 8150 then, for each window, sets those samples of theautocorrelation function whose values are less than the threshold tozero. Generally, the process 8150 removes small “noisy” values from theautocorrelation of each window, leaving only the “significant” featuresof the autocorrelation.

The final process 8160 determines whether each window containsartefacts. To do this, process 8160 compares the autocorrelationfunction (thresholded at process 8150) of a current window with theautocorrelation functions of a plurality of other windows (e.g., some orall other windows). In one implementation, the metric of comparisonbetween two autocorrelation functions is the cosine function, computedas the dot product of the two autocorrelation functions divided by theproduct of their respective Euclidean norms. The cosine function rangesbetween 0 (for wholly dissimilar functions) and 1 (for identicalfunctions). Process 8160 averages this metric for the similarity of thecurrent window to other windows over the plurality of other windows toobtain a “normality” metric for the current window. If the normalitymetric for the current window falls below a threshold (e.g. 0.95), thisindicates the current window is “outlying” enough to be discarded as anartefact.

FIG. 9 is a graph illustrating the operation of the method 8100 on anexample ECG signal. The graph contains an ECG trace 9000 lastingapproximately four minutes. Each vertical graticule shown in the bottomsignal trace of FIG. 9 represents thirty seconds. The other traces 9010to 9050 represent intermediate products of the method 8100 on the ECGtrace 9000. The trace 9010 represents the band-pass filtered ECG fromprocess 8110. The trace 9020 represents the derivative of the band-passfiltered ECG from process 8120. The trace 9030 represents the square ofthe derivative of the band-pass filtered ECG from process 8120. Thetrace 9040 represents the upper envelope of the square of the derivativeof the band-pass filtered ECG from process 8130. The trace 9050represents the “normality” metric of the envelope computed as part ofprocess 8160. The binary-valued trace 9060 is high for “outlying”windows whose normality metric falls below 0.95, and 0 otherwise. It maybe seen that the trace 9060 is high for two windows 9070 and 9080, bothof which coincide with patterns of unusual activity in the ECG trace9000, while the remainder of the ECG trace 9000 is relativelystationary.

Returning to the method 8000, the ECG signal, though primarilyrepresentative of heart activity, contains a component that is relatedto respiration. Process 8007 therefore extracts the respiratory-relatedcomponent of the artefact-removed ECG signal, resulting in an EDR(ECG-derived respiratory) signal. In one implementation, process 8007generates the EDR based on a determination of the amplitude of theR-wave of the ECG signal. In another implementation, process 8007generates the EDR based on a determination of the area covered by theQRS complex of the ECG signal.

Process 8010 of the method 8000 evaluates the artefact-removed ECGsignal to estimate the respiratory rate of the patient 1000. In oneform, process 8010 applies a wavelet-based approach. In another form,process 8010 applies a combination of any two or more ofdifferentiation, moving-average, and thresholding of the ECG signal.

Process 8015 evaluates the estimated respiratory rate from process 8010and the artefact-removed ECG signal from process 8005 to detect the AFibburden of the patient (a measure of irregularity of the heart rhythm oratrial fibrillation and a classification of the type of irregularity:paroxysmal, persistent, or permanent).

Process 8020 removes artefacts from the 3D accelerometry signalgenerated by the accelerometer 7172. Process 8025 then evaluates theartefact-removed 3D accelerometry signal to estimate posture (e.g.prone, supine, upright), based on the absolute vertical directionprovided by the accelerometer. For this step, the orientation of theaxes of the accelerometer 7172 relative to the main axes of the body maybe taken into account.

Process 8027 evaluates the artefact-removed 3D accelerometry signal toestimate respiratory effort. In one implementation, process 8027 appliesa principal component analysis (PCA)-based method to the 3Daccelerometry signal. For this step, the orientation of the axes of theaccelerometer 7172 relative to the main axes of the body may be takeninto account.

Process 8030 evaluates the artefact-removed 3D accelerometry signal tocompute an activity index representative of the non-cardio-respiratoryactivity of the body, e.g. activity resulting from gross bodily motion.

Process 8035 segments the “heart sounds” acoustic signal from theacoustic sensor 7178. The segmentation partitions the acoustic signalinto individual heart cycles and phases of each cycle (S1, systole, S2,diastole). Example implementations of process 8035 may apply any one ormore of wavelet decomposition, Shannon energy, and peak location.Process 8040 then extracts heart sound features from the segmented heartsounds signal provided by the segmentation process 8035. Process 8040may extract time domain features such as duration and amplitude, andfrequency domain features such as power spectral density.

Processes 8005 to 8040 may be carried out in parallel or sequentially inany order, with the exceptions that process 8015 should follow processes8005 and 8010, process 8007 should follow process 8005, processes 8025,8027, and 8030 should follow process 8020, and process 8040 shouldfollow process 8035.

Process 8045 evaluates the artefact-removed ECG signal from process8005, the posture estimate from process 8025, the respiratory effortestimate from process 8027, the activity index from step 8030, theoxygen saturation (SpO₂) signal from the PPG 7174, the skin temperaturesignal from the temperature sensor 7176, and the sympathetic activitysignal from the GSR sensor 7180 to estimate the sleep stage of thepatient (e.g. wake, REM, non-REM (NREM)). Process 8045 may also detectbrief arousals within the non-REM and REM stages. In one implementation,process 8045 extracts one or more features from its input signals,followed by classification such as by linear discriminant analysis(LDA), a support vector machine (SVM), or neural network to estimate thesleep stage and detect arousals.

Following process 8045, process 8050 evaluates the EDR signal and therespiratory rate estimate from processes 8005 and 8010, the postureestimate, the respiratory effort estimate, and the activity index fromprocesses 8025, 8027, and 8030, and the SpO₂ signal from the PPG 7174 todetect SDB events, e.g., apneas and hypopneas (undifferentiated fromeach other). Process 8050 may also consider the estimated sleep stagefrom process 8045. In one implementation, process 8050 extracts featuresfrom its input signals and applies a classifier to the features todiscriminate between normal breathing and SDB events in each ofsuccessive time windows, e.g. of duration 60 seconds or otherpredetermined window duration on the order of seconds or minutes.

Process 8060 classifies the detected SDB events from process 8050 intoapneas and hypopneas, and into open airway and closed airway(obstructive) events, by evaluation of the SpO₂ signal from the PPG7174, the sympathetic activity signal from the GSR sensor 7180, and theheart sound features extracted by process 8040. In one example ofclassification, an obstructive event may trigger sympathetic driveresulting in increased amplitude of heart sound(s) during the S1 phaseof each heart cycle. An event coinciding with increased amplitude ofheart sound(s) during the S1 phase of each heart cycle may therefore beclassified as obstructive.

Process 8070 considers the detected events from process 8050 and theirclassifications from process 8060 and detects Cheyne-Stoke respiration(CSR) and (optionally) other forms of periodic breathing (PB). Process8060 may be based on the sequencing and periodicity of the classifiedSDB events, and may also apply template matching of the EDR signal (fromprocess 8005) during hyperpneas with a sinusoidal template in itsevaluation.

From the classified SDB events from process 8060 and/or the CSR/PBdetections from process 8070, various indices of SDB severity may becomputed over a screening/diagnosis/monitoring session, e.g.apnea/hypopnea index (AHI), total duration of CSR episodes, etc. Thecomputation of the indices may take into account the total sleep time(TST) of the patient during the session, as estimated from the sleepstage information provided by process 8045. The computed indices may beused for screening, diagnostic, or monitoring purposes in conventionalfashion.

5.8 Glossary

For the purposes of the present technology disclosure, in certain formsof the present technology, one or more of the following definitions mayapply. In other forms of the present technology, alternative definitionsmay apply.

5.8.1 General

Air: In certain forms of the present technology, air may be taken tomean atmospheric air, and in other forms of the present technology airmay be taken to mean some other combination of breathable gases, e.g.atmospheric air enriched with oxygen.

Ambient: In certain forms of the present technology, the term ambientwill be taken to mean (i) external of the treatment system or patient,and (ii) immediately surrounding the treatment system or patient.

Continuous Positive Airway Pressure (CPAP) therapy: Respiratory pressuretherapy in which the treatment pressure is approximately constantthrough a respiratory cycle of a patient. In some forms, the pressure atthe entrance to the airways will be slightly higher during exhalation,and slightly lower during inhalation. In some forms, the pressure willvary between different respiratory cycles of the patient, for example,being increased in response to detection of indications of partial upperairway obstruction, and decreased in the absence of indications ofpartial upper airway obstruction.

Flow rate: The volume (or mass) of air delivered per unit time. Flowrate may refer to an instantaneous quantity. In some cases, a referenceto flow rate will be a reference to a scalar quantity, namely a quantityhaving magnitude only. In other cases, a reference to flow rate will bea reference to a vector quantity, namely a quantity having bothmagnitude and direction. Flow rate may be given the symbol Q. ‘Flowrate’ is sometimes shortened to simply ‘flow’.

Patient: A person, whether or not they are suffering from a respiratorycondition.

Pressure: Force per unit area. Pressure may be expressed in a range ofunits, including cmH₂O, g-f/cm² and hectopascal. 1 cmH₂O is equal to 1g-f/cm² and is approximately 0.98 hectopascal. In this specification,unless otherwise stated, pressure is given in units of cmH₂O.

Respiratory Pressure Therapy (RPT): The application of a supply of airto an entrance to the airways at a treatment pressure that is typicallypositive with respect to atmosphere.

5.8.2 Respiratory Cycle

Apnea: According to some definitions, an apnea is said to have occurredwhen flow falls below a predetermined threshold for a duration, e.g. 10seconds. An obstructive apnea will be said to have occurred when,despite patient effort, some obstruction of the airway does not allowair to flow. A central apnea will be said to have occurred when an apneais detected that is due to a reduction in breathing effort, or theabsence of breathing effort, despite the airway being patent. A mixedapnea occurs when a reduction or absence of breathing effort coincideswith an obstructed airway.

Breathing rate (respiratory rate): The rate of spontaneous respirationof a patient, usually measured in breaths per minute.

Duty cycle: The ratio of inhalation time, Ti to total breath time, Ttot.

Effort (breathing): The work done by a spontaneously breathing personattempting to breathe.

Expiratory portion of a breathing cycle: The period from the start ofexpiratory flow to the start of inspiratory flow.

Flow limitation: Flow limitation will be taken to be the state ofaffairs in a patient's respiration where an increase in effort by thepatient does not give rise to a corresponding increase in flow. Whereflow limitation occurs during an inspiratory portion of the breathingcycle it may be described as inspiratory flow limitation. Where flowlimitation occurs during an expiratory portion of the breathing cycle itmay be described as expiratory flow limitation.

Types of flow limited inspiratory waveforms:

(i) Flattened: Having a rise followed by a relatively flat portion,followed by a fall.

(ii) M-shaped: Having two local peaks, one at the leading edge, and oneat the trailing edge, and a relatively flat portion between the twopeaks.

(iii) Chair-shaped: Having a single local peak, the peak being at theleading edge, followed by a relatively flat portion.

(iv) Reverse-chair shaped: Having a relatively flat portion followed bysingle local peak, the peak being at the trailing edge.

Hypopnea: According to some definitions, a hypopnea is taken to be areduction in flow, but not a cessation of flow. In one form, a hypopneamay be said to have occurred when there is a reduction in flow below athreshold rate for a duration. A central hypopnea will be said to haveoccurred when a hypopnea is detected that is due to a reduction inbreathing effort. In one form in adults, either of the following may beregarded as being hypopneas:

-   -   (i) a 30% reduction in patient breathing for at least 10 seconds        plus an associated 4% desaturation; or    -   (ii) a reduction in patient breathing (but less than 50%) for at        least 10 seconds, with an associated desaturation of at least 3%        or an arousal.

Hyperpnea: An increase in flow to a level higher than normal.

Inspiratory portion of a breathing cycle: The period from the start ofinspiratory flow to the start of expiratory flow will be taken to be theinspiratory portion of a breathing cycle.

Patency (airway): The degree of the airway being open, or the extent towhich the airway is open. A patent airway is open. Airway patency may bequantified, for example with a value of one (1) being patent, and avalue of zero (0), being closed (obstructed).

Positive End-Expiratory Pressure (PEEP): The pressure above atmospherein the lungs that exists at the end of expiration.

Peak flow rate (Qpeak): The maximum value of flow rate during theinspiratory portion of the respiratory flow waveform.

Respiratory flow rate, patient airflow rate, respiratory airflow rate(Qr): These terms may be understood to refer to the RPT device'sestimate of respiratory airflow rate, as opposed to “true respiratoryflow rate” or “true respiratory airflow rate”, which is the actualrespiratory flow rate experienced by the patient, usually expressed inlitres per minute.

Tidal volume (Vt): The volume of air inhaled or exhaled during normalbreathing, when extra effort is not applied.

(inhalation) Time (Ti): The duration of the inspiratory portion of therespiratory flow rate waveform.

(exhalation) Time (Te): The duration of the expiratory portion of therespiratory flow rate waveform.

(total) Time (Ttot): The total duration between the start of oneinspiratory portion of a respiratory flow rate waveform and the start ofthe following inspiratory portion of the respiratory flow rate waveform.

Typical recent ventilation: The value of ventilation around which recentvalues of ventilation Vent over some predetermined timescale tend tocluster, that is, a measure of the central tendency of the recent valuesof ventilation.

Upper airway obstruction (UAO): includes both partial and total upperairway obstruction. This may be associated with a state of flowlimitation, in which the flow rate increases only slightly or may evendecrease as the pressure difference across the upper airway increases(Starling resistor behaviour).

Ventilation (Vent): A measure of a rate of gas being exchanged by thepatient's respiratory system. Measures of ventilation may include one orboth of inspiratory and expiratory flow, per unit time. When expressedas a volume per minute, this quantity is often referred to as “minuteventilation”. Minute ventilation is sometimes given simply as a volume,understood to be the volume per minute.

5.9 Other Remarks

A portion of the disclosure of this patent document contains materialwhich is subject to copyright protection. The copyright owner has noobjection to the facsimile reproduction by anyone of the patent documentor the patent disclosure, as it appears in Patent Office patent files orrecords, but otherwise reserves all copyright rights whatsoever.

Unless the context clearly dictates otherwise and where a range ofvalues is provided, it is understood that each intervening value, to thetenth of the unit of the lower limit, between the upper and lower limitof that range, and any other stated or intervening value in that statedrange is encompassed within the technology. The upper and lower limitsof these intervening ranges, which may be independently included in theintervening ranges, are also encompassed within the technology, subjectto any specifically excluded limit in the stated range. Where the statedrange includes one or both of the limits, ranges excluding either orboth of those included limits are also included in the technology.

Furthermore, where a value or values are stated herein as beingimplemented as part of the technology, it is understood that such valuesmay be approximated, unless otherwise stated, and such values may beutilized to any suitable significant digit to the extent that apractical technical implementation may permit or require it.

Unless defined otherwise, all technical and scientific terms used hereinhave the same meaning as commonly understood by one of ordinary skill inthe art to which this technology belongs. Although any methods andmaterials similar or equivalent to those described herein can also beused in the practice or testing of the present technology, a limitednumber of the exemplary methods and materials are described herein.

When a particular material is identified as being used to construct acomponent, obvious alternative materials with similar properties may beused as a substitute. Furthermore, unless specified to the contrary, anyand all components herein described are understood to be capable ofbeing manufactured and, as such, may be manufactured together orseparately.

It must be noted that as used herein and in the appended claims, thesingular forms “a”, “an”, and “the” include their plural equivalents,unless the context clearly dictates otherwise.

All publications mentioned herein are incorporated herein by referencein their entirety to disclose and describe the methods and/or materialswhich are the subject of those publications. The publications discussedherein are provided solely for their disclosure prior to the filing dateof the present application. Nothing herein is to be construed as anadmission that the present technology is not entitled to antedate suchpublication by virtue of prior invention. Further, the dates ofpublication provided may be different from the actual publication dates,which may need to be independently confirmed.

The terms “comprises” and “comprising” should be interpreted asreferring to elements, components, or steps in a non-exclusive manner,indicating that the referenced elements, components, or steps may bepresent, or utilized, or combined with other elements, components, orsteps that are not expressly referenced.

The subject headings used in the detailed description are included onlyfor the ease of reference of the reader and should not be used to limitthe subject matter found throughout the disclosure or the claims. Thesubject headings should not be used in construing the scope of theclaims or the claim limitations.

Although the technology herein has been described with reference toparticular examples, it is to be understood that these examples aremerely illustrative of the principles and applications of thetechnology. In some instances, the terminology and symbols may implyspecific details that are not required to practice the technology. Forexample, although the terms “first” and “second” may be used, unlessotherwise specified, they are not intended to indicate any order but maybe utilised to distinguish between distinct elements. Furthermore,although process steps in the methodologies may be described orillustrated in an order, such an ordering is not required. Those skilledin the art will recognize that such ordering may be modified and/oraspects thereof may be conducted concurrently or even synchronously.

It is therefore to be understood that numerous modifications may be madeto the illustrative examples and that other arrangements may be devisedwithout departing from the spirit and scope of the technology.

5.10 Reference Signs List

-   -   patient 1000    -   bed partner 1100    -   headbox 2000    -   ground electrode 2010    -   EOG electrode 2015    -   EEG electrode 2020    -   ECG electrode 2025    -   submental EMG electrode 2030    -   snore sensor 2035    -   thoracic movement sensor 2040    -   abdominal movement sensor 2045    -   oro-nasal cannula 2050    -   photoplethysmograph 2055    -   body position sensor 2060    -   patient interface 3000    -   seal-forming structure 3100    -   plenum chamber 3200    -   structure 3300    -   vent 3400    -   connection port 3600    -   forehead support 3700    -   RPT device 4000    -   external housing 4010    -   upper portion 4012    -   portion 4014    -   panels 4015    -   chassis 4016    -   handle 4018    -   pneumatic block 4020    -   inlet air filter 4112    -   blower 4142    -   air circuit 4170    -   electrical components 4200    -   Printed Circuit Board Assembly 4202    -   electrical power supply 4210    -   input devices 4220    -   humidifier 5000    -   humidifier inlet 5002    -   humidifier outlet 5004    -   humidifier base 5006    -   humidifier reservoir 5110 humidifier reservoir dock 5130    -   heating element 5240    -   device 7100    -   processor 7110    -   communication interface 7120    -   memory 7130    -   data 7140    -   code 7150    -   sensor interface 7160    -   ECG sensor 7170    -   accelerometer 7172    -   PPG 7174    -   temperature sensor 7176    -   acoustic sensor 7178    -   GSR sensor 7180    -   method 8000    -   process 8005    -   process 8010    -   process 8015    -   process 8020    -   process 8025    -   process 8027    -   process 8030    -   process 8035    -   process 8040    -   process 8045    -   process 8050    -   process 8060    -   process 8070    -   method 8100    -   process 8110    -   process 8120    -   process 8130    -   process 8140    -   process 8150    -   process 8160    -   trace 9000    -   trace 9010    -   trace 9020    -   trace 9030    -   trace 9040    -   trace 9050    -   trace 9060    -   window 9070    -   window 9080

1. A system comprising: at least one of an electrocardiogram (ECG)sensor or a photoplethysmograph (PPG); at least one of a galvanic skinresponse (GSR) sensor or an acoustic sensor; one or more processors; anda memory comprising instructions adapted to configure the one or moreprocessors to classify one or more sleep-disordered breathing (SDB)events of a patient, wherein by the instructions, the one or moreprocessors are configured to: control an analysis of (a) at least one of(i) sympathetic activity data of the patient from a signal generated bythe GSR sensor or (ii) acoustic data representing heart sound of thepatient from a signal generated by the acoustic sensor and (b) at leastone of (i) ECG data of the patient from a signal generated by the ECGsensor or (ii) pulse oximetry data of the patient from a signalgenerated by the PPG; and classify the one or more SDB events intoapneas and hypopneas, and/or into open and closed airway events, basedon the analysis.
 2. The system according to claim 1 comprising the GSRsensor, wherein by the instructions, the one or more processors areconfigured to control the analysis of the sympathetic activity data. 3.The system according to claim 2, wherein (a) the at least one of the ECGsensor or the PPG and (b) the GSR sensor are co-located in one device.4. The system according to claim 3, wherein the device is configured asa patch adapted to be worn on skin of a chest of the patient.
 5. Thesystem according to claim 1 further comprising an accelerometer, whereinby the instructions, the one or more processors are further configuredto control an analysis of accelerometry data of the patient from asignal generated by the accelerometer, and wherein the classification ofthe one or more SDB events is also based on the analysis of theaccelerometry data.
 6. The system according to claim 5, wherein theanalysis of the accelerometry data comprises estimating a posture of thepatient from the accelerometry data.
 7. The system according to claim 5,wherein the analysis of the accelerometry data comprises estimating arespiratory effort of the patient from the accelerometry data.
 8. Thesystem according to claim 5, wherein the analysis of the accelerometrydata comprises computing an activity index of the patient from theaccelerometry data, the activity index representing gross bodily motionof the patient.
 9. The system according to claim 1 comprising the PPG,wherein by the instructions, the one or more processors are configuredto control the analysis of the pulse oximetry data.
 10. The systemaccording to claim 1 comprising the ECG sensor, wherein by theinstructions, the one or more processors are configured to control theanalysis of the ECG data.
 11. The system according to claim 10, whereinthe analysis of the ECG data comprises estimating a respiratory ratefrom artefact-removed ECG data.
 12. The system according to claim 10,wherein the analysis of the ECG data comprises removing artefacts fromthe ECG data to produce artefact-removed ECG data.
 13. The systemaccording to claim 12, wherein the removing of the artefacts from theECG data comprises identifying portions of the ECG data that differ froma typical portion.
 14. The system according to claim 13, wherein theidentifying of the portions of the ECG data that differ from a typicalportion comprises comparing autocorrelation functions of a plurality ofwindows derived from the signal generated by the ECG sensor.
 15. Thesystem according to claim 14, wherein a metric of comparison between twoautocorrelation functions is a cosine function.
 16. The system accordingto claim 15, wherein the cosine function is computed as a dot product ofthe two autocorrelation functions divided by a product of theirrespective Euclidean norms.
 17. The system according to claim 12,wherein the removing of the artefacts from the ECG data comprises:filtering the signal generated by the ECG sensor; and differentiatingand squaring the filtered signal.
 18. The system according to claim 17,wherein the removing of the artefacts from the ECG data furthercomprises finding an envelope of the squared derivative of the filteredsignal.
 19. The system according to claim 18, wherein the removing ofthe artefacts from the ECG data further comprises: partitioning theenvelope into a plurality of windows; and computing an autocorrelationfunction for each of the windows.
 20. The system according to claim 19,wherein each window has a fixed duration.
 21. The system according toclaim 19, wherein the removing of the artefacts from the ECG datafurther comprises: computing a threshold by averaging peak values of theautocorrelation functions; and adjusting at least some samples of theautocorrelation functions based on comparisons between those samples andthe threshold.
 22. The system according to claim 19, wherein theremoving of the artefacts from the ECG data further comprises comparingthe autocorrelation functions to determine whether one or more of theplurality of windows contain artefacts.
 23. The system according toclaim 1 comprising the acoustic sensor, wherein by the instructions, theone or more processors are configured to control the analysis of theacoustic data.
 24. The system according to claim 23, wherein theclassifying of the one or more SDB events comprises: segmenting theacoustic data into phases of each heart cycle; and extracting heartsound features from the segmented acoustic data.
 25. The systemaccording to claim 1, wherein by the instructions, the one or moreprocessors are further configured to detect Cheyne-Stokes respiration(CSR) from the one or more classified SDB events.
 26. The systemaccording to claim 25, wherein the detecting of CSR comprises templatematching of a respiratory-related component extracted from the ECG data.27. The system according to claim 1, wherein by the instructions, theone or more processors are further configured to control a change to atherapy provided by a therapy device based on the one or more classifiedSDB events.
 28. A method of classifying one or more sleep-disorderedbreathing (SDB) events of a patient, the method comprising: controlling,in one or more processors, an analysis of (a) at least one of (i)sympathetic activity data of the patient from a signal generated by agalvanic skin response (GSR) sensor or (ii) acoustic data representingheart sound of the patient from a signal generated by an acoustic sensorand (b) at least one of (i) electrocardiogram (ECG) data of the patientfrom a signal generated by an ECG sensor or (ii) pulse oximetry data ofthe patient from a signal generated by a photoplethysmograph (PPG);classifying, in the one or more processors, one or more SDB events intoapneas and hypopneas, and/or into open and closed airway events, basedon the analysis; and generating, in the one or more processors, anoutput indication of the one or more classified SDB events.
 29. Aprocessor-readable medium, having stored thereon processor-executableinstructions which, when executed by a processor, cause the processor toclassify sleep-disordered breathing (SDB) events according to the methodof claim
 28. 30. An apparatus comprising: means for generating at leastone of (a) electrocardiogram (ECG) data of a patient or (b) pulseoximetry data of the patient; means for generating at least one of (a)sympathetic activity data of the patient or (b) acoustic datarepresenting heart sound of the patient; and means for analysing (a) atleast one of (i) the sympathetic activity data of the patient or (ii)the acoustic data representing heart sound of the patient and (b) atleast one of (i) the ECG data of the patient or (ii) the pulse oximetrydata of the patient to classify one or more sleep-disordered breathing(SDB) events of the patient into apneas and hypopneas, and/or into openand closed airway events.